🎁 Before you apply, rehearse this interview. Create your free WorkMundi account and get an Interview Training on HelpsYouSpeak — no cost, no card. I want my training →
AI Engineer— AI-First Product Builder Worksmith Solutions | Full-Time | Remote / Hybrid About Worksmith Solutions Worksmith is a fast-growing AI consulting, growth and technology firm helping clients build scalable systems, automate operations, and grow through technology. We move fast, build smart, and leverage cutting-edge AI tools to deliver work that would take traditional agencies 3x longer. We're all about speed, accuracy, and perfection! The Role We're looking for a Tech Lead who builds with AI at the center, not as an afterthought. You'll be responsible for architecting and shipping full-stack digital products — from CRM systems and patient portals to automation pipelines and mobile apps — using AI (ideally Claude by Anthropic) as a core productivity multiplier across the entire development lifecycle. This is not a role for someone who uses AI occasionally. We want someone who thinks in prompts, designs agentic systems the way others design databases, ships in sprints, and solves problems before they become tickets. Our website — worksmith.tech What You'll Build Based on our active client roadmap, you'll be delivering: Business Health Check — a financial and operational diagnostic for businesses: automated reconciliation and leakage detection across procurement, site cash control, labour, and collections, delivered as a measured, evidenced finding CA Workflow Automation — practice automation for Chartered Accountant firms, priced per entity under management: GSTR-2B reconciliation, ITC risk monitoring, and Tally/Zoho-integrated workflows across a firm's full client book Operational Intelligence Agents — the multi-agent system underpinning both products above, including agents that write back into a client's live accounting system under guardrails, not just read and report AI-Powered Internal Tools — Claude-driven agents for content generation, reporting, and internal workflow automation Core Responsibilities CRM Systems — custom-built data systems with referral tracking, follow-up automation, and dashboards Web Portals — patient portals, doctor portals, and corporate health dashboards Mobile Applications — cross-platform apps for appointment booking, records access, and push notifications Marketing & Lead Gen Tech — landing pages, WhatsApp automation pipelines, lead funnels SEO & Analytics Infrastructure — structured data, performance tracking, conversion dashboards WhatsApp & Email Automation — multi-step nurturing sequences and consultation scheduling bots Lead end-to-end technical architecture and delivery of client projects Use Claude (Anthropic API) as a primary tool for: code generation, debugging, documentation, content automation, prompt-driven UI scaffolding, and internal tooling (including your programming knowledge and edits wherever needed) Design, evaluate, and iterate on prompt architectures, agentic workflows, and RAG pipelines for internal and client-facing AI systems Own the reconciliation and leakage-detection engine behind the Business Health Check, and the GST/entity-based automation behind the CA Workflow product — these are the two flagship AI systems, not internal tooling Own AI system quality — build lightweight eval harnesses, monitor for hallucination or drift, and enforce guardrails against prompt injection and data leakage, especially on healthcare-adjacent and financial-data products Build and maintain full-stack applications with clean, scalable code Design and integrate databases, APIs, and third-party services Automate repetitive dev and business workflows using AI agents Collaborate with design and strategy teams to ship fast without cutting corners Set up CI/CD pipelines, version control practices, and deployment workflows Mentor and establish team coding standards, including how the team prompts, evaluates, and ships AI-assisted code Required Technical Skills Reworked around what an AI Engineer building production LLM systems actually needs day to day, plus the gaps specific to Worksmith's product surface (mobile, technical SEO, health data, and the health-check / CA workflow product line). AI/LLM engineering is now the lead skill set — full-stack ability is the delivery mechanism around it, not a separate track. AI / LLM Engineering LLM APIs & Tooling — Anthropic Claude API (Messages API, tool use / function calling, prompt caching, extended thinking); working familiarity with OpenAI or Gemini APIs a plus Prompt & Context Engineering — system prompt design, few-shot patterning, context-window and token-budget management Agentic Systems — building multi-step, tool-using agents (Claude Agent SDK, LangChain / LangGraph, CrewAI, or custom orchestration) RAG & Vector Search — embeddings, chunking strategy, vector databases (Pinecone, Weaviate, pgvector, Chroma) Structured Outputs & Tool Schemas — JSON Schema design, function-calling contracts, output validation and retry logic AI Evaluation & Observability — eval harnesses, tracing and logging (LangSmith, Helicone, or custom scripts), regression testing for prompts Model Selection & Cost/Latency Tradeoffs — knowing when to prompt vs. retrieve vs. fine-tune, and picking the right model tier per task AI Security & Guardrails — prompt-injection defense, PII/PHI leakage prevention, least-privilege sandboxing of agent tool access Financial & Operational Intelligence Systems Python — primary language for AI integrations, automation, scripting, and data processing JavaScript / TypeScript — primary language for frontend and backend HTML5 / CSS3 — pixel-perfect UI implementation SQL — relational database queries, schema design (PostgreSQL / MySQL) Bash / Shell — server automation and DevOps scripting Frontend React.js or Next.js — SSR, dynamic routing, API routes Tailwind CSS — or equivalent utility-first CSS Responsive and mobile-first design implementation Backend Node.js / Express or FastAPI (Python) — FastAPI preferred where the service is AI-heavy RESTful API design and GraphQL basics Authentication systems (JWT, OAuth2) Mobile (new — matches the Mobile Applications deliverable, previously unlisted) React Native or Flutter — cross-platform mobile development Push notification services (Firebase Cloud Messaging / APNs) App store deployment and release management (Apple App Store, Google Play) Databases & Storage PostgreSQL / MySQL — relational data modeling MongoDB or Firebase — NoSQL for flexible schemas Redis — caching and session management Vector stores — pgvector, Pinecone, Weaviate, or Chroma for embeddings and semantic search DevOps & Deployment Docker — containerization GitHub Actions or similar CI/CD pipelines Vercel / AWS / GCP — cloud deployment Linux server management basics Integrations & Automation Nice to Have A shipped AI agent or LLM-powered product in production, not just a prototype Prior experience in a fast-paced agency or consulting environment juggling multiple client codebases Comfort making architecture calls with incomplete specs and tight timelines
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.